Rate My Professor Yuan Yuan

Yuan Yuan is a tenure-track Assistant Professor of Computer Science at Boston College's Morrissey School of Arts and Sciences, having joined the faculty in January 2024. Previously, she served as a Postdoctoral Research Associate at the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory (CSAIL), working with Professor Dina Katabi. She earned her Ph.D. in Electronic and Computer Engineering from the Hong Kong University of Science and Technology, advised by Professor Dit-Yan Yeung, and was a visiting research scholar at the Robotics Institute of Carnegie Mellon University with Professor Abhinav Gupta. Yuan holds a B.S. from Huazhong University of Science and Technology. Throughout her career, she has received numerous honors, including selection for the Rising Stars in AI Symposium at KAUST (2023), Ali Star from Alibaba Group (2019), Microsoft Young Fellowship from Microsoft Research Asia (2011), National Scholarships from the Ministry of Education of P.R. China (2009, 2010, 2011), and various research travel grants from HKUST and CMU.

Yuan Yuan's research focuses on deep learning, computer vision, multisensory and generative AI, AI for medicine, health, and science, including digital biomarker discovery and contactless health monitoring, as well as trustworthy and safe AI emphasizing interpretability, robustness, and alignment. A pivotal contribution is her work on an AI-powered digital biomarker for Parkinson's disease diagnosis and progression tracking from nocturnal breathing signals, published as "Artificial Intelligence Detects Parkinson’s Disease and Estimates Disease Severity and Progression from Nocturnal Breathing" in Nature Medicine (2022), which was named one of the top ten notable advances in medicine of 2022 and covered by Forbes, The Washington Post, BBC, TechCrunch, and Engadget. Key publications also include "TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut" (IEEE TPAMI, 2023), "Continuous Invariance Learning" (ICLR, 2024), "Targeted Supervised Contrastive Learning for Long-Tailed Recognition" (CVPR, 2022), "Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut" (CVPR, 2022), and "Temporal Dynamic Graph LSTM for Action-driven Video Object Detection" (ICCV, 2017). She contributes as a program committee member and reviewer for conferences like CVPR, ICCV, NeurIPS, ICLR, ICML, ECCV, and journals such as IEEE TPAMI, TIP, TCSVT, TMM, and TNNLS. At Boston College, she teaches CSCI 3370 Deep Learning, CSCI 3345 Machine Learning, and CSCI 3399 Vision and Learning.